Research On Dynamic Vehicle Routing Problem Of City Logistics Based On Floating Car Data

With the development of e-commerce, the all-round optimization distribution routes,improve of distribution efficiency and quality of service requirements in city logisticsdistribution is imperative. Getting accurate real-time dynamic traffic information is neededas the basic requirement to use traffic information to make vehicle routing and timearrangement. In order to achieve this, we rely on floating car data analysis and provide theresources to deal with time-dependent travel time.The content of this article is that we collect raw floating car data pre-process,map-match and make travel time estimation and prediction, to get real-time dynamictravel time which our vehicle routing need. As for simplified urban dynamic vehiclerouting problem of logistics, we can set a single trip travel time of the shortest pathproblem model. As for the model solution, this article uses the greedy algorithm to helptruck driver determine the next node as the target node, which is also the shortest traveltime far from the current node. And then use the dijkstra algorithm to choose the minimalpath from the current node to the next target node. When going to start from the currentnode, truck drivers need to make real-time dynamic path selection by preprocessing theraw floating car data and estimating the road travel time. This combination of locallyoptimal path between nodes is the full path to the end of city logistics distribution vehicle.